The clinical heterogeneity of human hepatocellular carcinoma (HCC) and the lack of good diagnostic markers and treatment strategies have rendered the disease a major challenge. Patients with HCC have a highly variable clinical course indicating that HCC comprises several biologically distinctive subgroups. We hypothesized that the prognostic variability likely reflects a molecular heterogeneity of tumors. In the process of testing this hypothesis we have asked if a gene expression signatures specific for TGF-beta signaling pathway could refine the diagnosis and/or prognostic predictions of HCC patients. Since TGF-beta exhibits tumor stage dependent suppressive (i.e. growth inhibition) and oncogenic (i.e. invasiveness) properties, a TGF-beta&#61472;gene expression signature may contain gene sets characteristic for these properties and thus be relevant for the molecular classification of the tumors. Applying a comparative functional genomic approach we demonstrated that temporal TGF-beta&#61472;gene expression signatures established in mouse primary hepatocytes successfully discriminated distinct subgroups of HCC. The TGF-beta positive cluster highlighted two independent, early (1-2 hours) and late (4-24 hours), TGF-beta signatures. To evaluate the clinical significance of TGF-beta signature in the molecular classification of HCC, we then compared the distribution of several clinical and pathological variables between HCC harboring early or late TGF-beta signatures. Kaplan-Meier plots and log-rank statistics indicated that the patients with a late TGF-beta signature showed a significantly (P < 0.005) shortened mean survival time (16.2 5.3 months) compared to the patients with an early (60.7 16.1 months) TGF-beta signature. Also, tumors expressing late TGF-beta&#61472;responsive genes displayed an invasive phenotype and an increased tumor recurrence. Furthermore, we demonstrated that the TGF-beta gene expression signature possess a predictive value for tumors other than HCC and therefore open new avenues for novel TGF-beta based therapeutic approaches. HCC is considered a hypervascular tumor, and expression of the hypoxia inducible factor (HIF) and its target genes has been reported to be associated with a poor prognosis phenotype. Using a comparative genomics approach, we have characterized the hypoxic gene expression profile in freshly isolated mouse hepatocytes, with the aim of using this profile to explore the importance of the hypoxic response in HCC. Culture of mouse hepatocytes under hypoxic conditions over 24 hours revealed more than 1800 significant (p<0.001) regulated genes. In the first 12 hours the most important response to the hypoxic conditions is the upregulation of genes involved in angiogenesis, blood vessel formation and blood coagulation, while the transition to an anaerobic metabolism seems to be the most important response after 24 hours. Genes that showed at least 2 fold expression difference between hypoxic and normoxic conditions were selected to define the hypoxia gene expression signature. 504 orthologous genes derived from the hypoxic signature were used to perform hierarchical cluster analysis of 139 human HCC. As a result, two subsets of genes were identified. One subset of 104 genes implicated in cell cycle and apoptosis regulation (e.g. Gadd45a, Cdk4, Map4k4, Dusp1, Csk2), blood coagulation (e.g. Plg, F2, F9, F13b, Hc, Agt, Serpinc1, Serpinf1) and immune response (e.g. C1r, C8a, C8b, C8g, C9, Rarres2) among other functions, was able to predict HCC with a good prognosis. On the other hand, a subset of 62 genes, some of them involved in cell cycle progression (e.g. Cdk6, Ches1, Ccng1, Ngfb), apoptosis regulation (e.g. Bcl6b, Pik3r1) and angiogenesis (e.g. Vegf, Id3), was able to predict HCC with a poor prognosis. Interestingly, among these 62 genes, we identified some that have already been found to predict poor prognosis in other human cancers (Chin et al. PLoS Medicine. 2006 Mar; 3(3)). Further studies are aimed at characterizing the mechanisms by wich hypoxic conditions regulate these 2 sets of genes